code: def forward(self, x: Tensor, edge_index: Tensor) -> Tensor:
      x = self.conv1(x, edge_index).relu()
      x = self.dropout(x)
      x = self.conv2(x, edge_index).relu()
      x = self.dropout(x)
      return self.lin(x)
  
imports: import os.path
  from typing import Dict, List, Tuple
  import pytorch_lightning
  import torch
  import torch.nn.functional
  from pytorch_lightning import LightningModule, Trainer
  from pytorch_lightning.callbacks import ModelCheckpoint
  from torch import Tensor
  from torchmetrics import Accuracy
  import torch_geometric.transforms
  from torch_geometric.data import Batch
  from torch_geometric.data.lightning import LightningNodeData
  from torch_geometric.datasets import OGB_MAG
  from torch_geometric.nn import Linear, SAGEConv, to_hetero
  from torch_geometric.typing import EdgeType, NodeType
label_desc: Use image node_id 2 for calling the GNN obj's underlying member method code with example usage: obj.forward(x, edge_index) and returns: self